Bernard Ghanem

Publications204
h-index37
Citations7,230
Highly Influential Citations1,083
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The Visual Object Tracking VOT2016 Challenge Results
The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 70 trackers are… Expand
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ActivityNet: A large-scale video benchmark for human activity understanding
In spite of many dataset efforts for human action recognition, current computer vision algorithms are still severely limited in terms of the variability and complexity of the actions that they can… Expand
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A Benchmark and Simulator for UAV Tracking
In this paper, we propose a new aerial video dataset and benchmark for low altitude UAV target tracking, as well as, a photo-realistic UAV simulator that can be coupled with tracking methods. Our… Expand
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Robust visual tracking via multi-task sparse learning
In this paper, we formulate object tracking in a particle filter framework as a multi-task sparse learning problem, which we denote as Multi-Task Tracking (MTT). Since we model particles as linear… Expand
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Context-Aware Correlation Filter Tracking
Correlation filter (CF) based trackers have recently gained a lot of popularity due to their impressive performance on benchmark datasets, while maintaining high frame rates. A significant amount of… Expand
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TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild
Despite the numerous developments in object tracking, further improvement of current tracking algorithms is limited by small and mostly saturated datasets. As a matter of fact, data-hungry trackers… Expand
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DAPs: Deep Action Proposals for Action Understanding
Object proposals have contributed significantly to recent advances in object understanding in images. Inspired by the success of this approach, we introduce Deep Action Proposals (DAPs), an effective… Expand
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Maximum Margin Distance Learning for Dynamic Texture Recognition
The range space of dynamic textures spans spatiotemporal phenomena that vary along three fundamental dimensions: spatial texture, spatial texture layout, and dynamics. By describing each dimension… Expand
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Robust Visual Tracking via Structured Multi-Task Sparse Learning
In this paper, we formulate object tracking in a particle filter framework as a structured multi-task sparse learning problem, which we denote as Structured Multi-Task Tracking (S-MTT). Since we… Expand
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SST: Single-Stream Temporal Action Proposals
Our paper presents a new approach for temporal detection of human actions in long, untrimmed video sequences. We introduce Single-Stream Temporal Action Proposals (SST), a new effective and efficient… Expand
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